LLM tools like Claude Code have made generating code trivial, but building robust, maintainable software remains expensive and complex. The barrier to entry has collapsed, enabling non-developers to create personal, disposable tools for specific problems. However, real engineering value has shifted from writing syntax to understanding systems, architecture, and edge cases. While AI can accelerate development, it cannot replace the judgment, domain expertise, and technical oversight required to build scalable solutions. Distribution and product-market fit remain the primary challenges, not code generation.